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All Journal Jurnal TIMES Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Sisfokom (Sistem Informasi dan Komputer) Jiko (Jurnal Informatika dan komputer) JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Jurnal Informatika Kaputama (JIK) Jurnal Sistem Informasi Kaputama (JSIK) Jurnal Mantik Jusikom: Jurnal Sistem Informasi Ilmu Komputer Jurnal Sains dan Teknologi Jurnal Tekinkom (Teknik Informasi dan Komputer) INFOKUM Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Journal of Computer Networks, Architecture and High Performance Computing Jurnal Teknik Informatika (JUTIF) JURNAL MITRA PRIMA Jurnal Pengabdian kepada Masyarakat Politeknik Negeri Batam International Journal of Information System & Innovative Technology TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Journal of Deep Learning, Computer Vision and Digital Image Processing Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer International Journal of Information System and Innovative Technology INOVTEK Polbeng - Seri Informatika
Delima Sitanggang, Delima
Universitas Prima Indonesia
Aerospace Engineering Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Veterinary

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Classification of Hypertension Using Support Vector Machine Based on Data Photoplethysmography and Blood Pressure Estimator Glen Virdho Sirait; Anand Roshan; Delima Sitanggang; Reyhan Achmad Rizal
JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Vol. 8 No. 2 (2025): Jurnal Teknologi dan Ilmu Komputer Prima (JUTIKOMP)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jutikomp.v8i2.7658

Abstract

This study formulates a Support Vector Machine (SVM)-based hypertension classification model using physiological features from Photoplethysmograph (PPG) signals and systolicdiastolic blood pressure estimates. PPG data were collected from 276 participants in three locations using a non-invasive device integrated into the MR-IAT Robot Covid web platform. Feature extraction and preprocessing were performed in MATLAB, while SVM (scikit-learn) model training and testing were conducted in Google Colab. Comparison of three kernel variants—linear, quadratic, and cubic—showed that the cubic kernel was the most superior with an accuracy of 96.4%, followed by quadratic at 94.9% and linear at 91.3%. Overall, the model achieved 93.9% accuracy in distinguishing six blood pressure categories (Hypotension, Normal, Prehypertension, Stage 1 Hypertension, Stage 2 Hypertension, Crisis). Visualization of the results (scatter plot, confusion matrix, parallel coordinates) revealed that systolic pressure, diastolic pressure, age, weight, and respiration rate were the most influential parameters. These findings underscore the potential application of SVM in portable devices for early detection and real-time monitoring of hypertension.
Comparative Analysis of Linear Regression Algorithms and Random Forest for Skincare Product Sales Prediction of Skincare Products on the Tokopedia Marketplace Brian Colin Chang; Widodo Tjiawie; Jervis Patrick; Justine Thorino; Delima Sitanggang
JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Vol. 9 No. 1 (2026): Jurnal Teknologi dan Ilmu Komputer Prima (JUTIKOMP)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jutikomp.v9i1.7906

Abstract

This study aims to evaluate and compare the performance of Linear Regression and Random Forest algorithms in predicting skincare product sales on the Tokopedia platform. Accurate sales predictions play a strategic role for businesses, particularly in pricing policy formulation, product positioning, and more efficient inventory management. The data used included 7,217 skincare products with six main variables, which were then expanded into 21 features through preprocessing and feature engineering stages, including product type extraction, main benefits, seller characteristics, location tier, and price position category. The model was developed and tested using a training and testing data split with a ratio of 80:20. The analysis results showed that the Random Forest algorithm performed better than Linear Regression. In the test data, Random Forest achieved an R² value of 0.2115 with an RMSE of 32,754.23 and an MAE of 12,073.59. In contrast, Linear Regression only obtained an R² of 0.0245 with an RMSE of 36,431.74 and an MAE of 14,688.99. Although the R² value is relatively low, the results are still realistic considering the complexity of e-commerce sales behavior, which is influenced by various external factors. Feature importance analysis shows that price and price per unit are the most dominant factors, followed by rating, number of product benefits, brand category, and product type. Based on these findings, Random Forest is recommended as a more suitable model to support skincare product sales predictions on Tokopedia, mainly due to its ability to capture non-linear patterns and interactions between features. This study is expected to contribute to the development of data-driven marketing strategies, particularly in pricing, multi-benefit product development, and skincare portfolio management on marketplace platforms.
A Simple Anti-Cheat Technique to Prevent Speed ​​Hacks in FPS Games (Case Study: VALORANT with Counter-Strike 2) Derick Derick; Delima Sitanggang
Jurnal Sistem Informasi dan Ilmu Komputer Prima(JUSIKOM PRIMA) Vol. 10 No. 1 (2026): Jusikom: Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v10i1.8458

Abstract

Speed ​​hacking is a form of cheating in First-Person Shooter (FPS) games that causes players to move beyond normal limits, disrupting gameplay balance. This study analyzes simple anti-cheat techniques to detect and prevent speed hacking in Valorant and Counter-Strike 2. The methods used include literature review, conceptual observation, and rule-based simulations. This involves validating player speeds, limiting maximum speed values, and checking movement logic. Simulation results indicate that normal players have speeds of around 4.79 to 6.02 units/second, while players suspected of speed hacking reach speeds of 7.87 to 10.36 units/second. This difference suggests that speed thresholds can be an early indicator for detecting movement anomalies. Simple anti-cheat techniques do not replace complex commercial systems, but they can serve as a safe and easy-to-understand starting model for maintaining fair play in competitive FPS games. Keywords: anti-cheat, speed hack, FPS games, threshold, fair play
Co-Authors -, Amalia ., Calvin ., Efendy ., Kelvin Abdi Dharma Abdi Dharma Achmad Ridwan Ade Sahputra Nababan Agung Prabowo Agustinus Lumban Raja Albert Sagala, Albert Alvina, Jesslyn Ambarita, Rivandu Amir Mahmud Husein, Mawaddah Harahap, Amir Anand Roshan Angie, Vicky Anita Anita Anita Christine Sembiring Ayu Rahayu Sagala Ayu Rosalya Sagala Barus, Ertina Sabarita Bolon, Debby Novriyanti Br Tp. Brandon Lee Brian Colin Chang Bryan Wijaya Butarbutar, Serly Yunarti Christian Dwigo Cloudia Stevani Saragih Sumbayak Cristian Andika Tarigan Dahlian, Ryo Benhard Darren Lucius David David Debby Novriyanti Br Tp.Bolon Derick Derick Diasta Natanael Sembiring Eric Simon Giovanni Siahaan Ester Farida Simanjuntak Esther Mayorita Nababan Etriska Prananta S. Evta Indra Evta Indra Faijriah Nazla Sahira Federico Sanjaya Felix Felix Feri Herlangga Ginting, Arico Sempana Ginting, Nessa Sanjaya Ginting, Riski Titian Glen Virdho Sirait Grace Aloina Greace HS, Christnatalis Hutahaean, Rani Hutasoit, Feliks Daniel Immanuel Sinaga, Ferdy Indra, Evta Indren, Indren Intan Susanti Simarmata Jasmin William Natanael Sinaga Jefri Syah Putra Laoli Jervis Patrick Jesslyn Alvina Jorgi L.Tobing, Stefanus Juan Juanta, Palma Julio Putra Tarigan Justine Thorino Kumar, Sharen Lee, Brandon Lidya Silalahi Lumbantoruan, Nurima Manao, Sonatafati Manday, Dhanny Rukmana Mardi Turnip, Mardi Maria Yostin Br Tarigan Marlince N.K Nababan Marpaung, Aldo Andy Yoseph Tama Marpaung, Cantika Matthew Oullanley Lee Meri Natasia Napitupulu Michael Joan Mita Aprila Silpa Simanjuntak Muhammad Amsar Putra Muhammand Ridho Muliadi Marianus Sirait Musa Andrew Loyd Sitanggang Nababan, Marlince N.K Nainggolan, Winner Parluhutan Nanchy Adeliana Br S. Muham Napitupuluh, Christian Deniro Niken Sihombing Nina Purnasari Nova Riani Fransiska Novanius Lahagu Oktarino, Ade Oktoberto Perangin-angin Palma Juanta Perangin Angin, Despaleri Perangin-angin, Despaleri Pungki Laurensius Ritonga Putra, Muhammad Amsar Reyhan Achmad Rizal Reza Pahlevi Rijois I. E. Saragih Rinaldi Fauzan Rizal, Reyhan Achmad Sadarman Zebua Saljuna Hayu Rangkuti Sanjaya, Federico Saragi, Yosua Morales Sarah Simangunsong Saut Parsaoran Tamba sherly sherly Siahaan, Edivan Wasington Siahaan, Eric Simon Giovanni Sihotang, Putri Anasia Simangunsong, lamria Simanjuntak, Ester Farida Simanjuntak, Mega Herlin Simanjuntak, Ruth Marsaulina Simarmarta, Brando Benedictus Sinaga, Jasmin William Natanael Sion Putri Zalukhu Siregar, Saut Dohot Sitanggang, Maria Natalenta Siti Aisyah Siti Aisyah Sitompul, Chris Samuel Sitorus, Angelina Monica Situkkir, Miando Mangara Sri Wahyu Tarigan Sri Wahyuni Tarigan Sundah, Geertruida Frederika Suyanto, Jao Han Tampubolon, Irfan Saputra Tampubolon, Johanes Joys Ronaldo Tampubolon, Tasya Rouli Christy Tarigan, Julio Putra Tarigan, Nina Veronika Tarigan, Sri Wahyuni Tasya Rouli Christy Tampubolon Tifanny Tifanny Togar Timoteus Gultom Vicky Angie Widodo Tjiawie Wijaya, Bryan Wilbert Nyoman Wilbert Solo, Eddrick Winarti Pasaribu Yennimar Yennimar, Yennimar Yoga Tri Nugraha Yonata Laia Yosua Morales Saragi Zachary Djuli